Crowdsourcing Architectural Beauty: Online Photo Frequency Predicts Building Aesthetic Ratings.

The aesthetic quality of the built environment is of paramount importance to the quality of life of an increasingly urbanizing population. However, a lack of data has hindered the development of comprehensive measures of perceived architectural beauty.

In this paper, we demonstrate that the local frequencies of geotagged photos posted by internet users in two alternative photo-sharing websites strongly predict subjective aesthetic ratings of buildings. We conduct an independent aesthetic survey with respondents rating proprietary stock photos of 1,000 buildings across the United States. Buildings with higher ratings were found more likely to be geotagged with user-uploaded photos in both Google Maps and Flickr. This correlation also holds for the aesthetic rankings of raters who seldom upload materials to the Internet. Objective architectural characteristics that predict higher average beauty ratings of buildings also positively covary with their internet photo frequency. These results validate the use of very localized user-generated image uploads in panoramic sites to measure the aesthetic appeal of the urban environment in the study of architecture, real estate, urbanism, planning, and environmental psychology.



Joint with Albert Saiz and James Bernard.
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